强化学习
电压
马尔可夫决策过程
节点(物理)
计算机科学
灵敏度(控制系统)
过程(计算)
电压调节
马尔可夫过程
控制理论(社会学)
控制(管理)
工程类
电子工程
人工智能
电气工程
数学
统计
结构工程
操作系统
作者
Sihao Zhu,Fang Chen,Haozhe Yuan,Yuqian Tian,S.Y. Li
标识
DOI:10.1109/acpee60788.2024.10532354
摘要
The integration of Electric Vehicle (EV) and Distributed Generation (DG) introduces heightened uncertainties to distribution networks. To tackle the precision and real-time challenges inherent in conventional control methods employed for voltage control, this study proposes the Voltage Safety Layer-based Multi-Agent Deep Deterministic Policy Gradients (VSL-MADDPG) algorithm. Firstly, the active voltage optimization problem is reformulated as a Constrained Markov Decision Process (cMDP). Secondly, a Voltage Safety Layer based on the voltage sensitivity matrix is added to the MADDPG algorithm to mechanistically ensure the voltage security of the active distribution network. Finally, results of case simulations on the IEEE33 node system demonstrate that the proposed algorithm significantly reduces the network losses and the charging costs.
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